CK-12_Advanced_Probability_and_Statistics_Second_Edition_Volume_2 by CK-12 Foundation

Author:CK-12 Foundation
Language: eng
Format: epub
Publisher: CK-12 Foundation

Lesson Summary

Prediction is simply the process of estimating scores of one variable based on the scores of another variable. We use the least-squares regression line, or linear regression line, to predict the value of a variable.

Using this regression line, we are able to use the slope, -intercept, and the calculated regression coefficient to predict the scores of a variable. The predictions are represented by the variable .

When there is an exponential relationship between the variables, we can transform the data by taking the log of the dependent variable to achieve linearity between and . We can then fit a least squares regression line to the transformed data.

The differences between the actual and the predicted values are called residual values. We can construct scatterplots of these residual values to examine outliers and test for linearity.

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